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Ferreira, M. A. M. (2019). LAPLACE transform effectiveness in the M/G/oo queue busy period probabilistic study. In Dagmar Szarková, Daniela Richtáriková, Peter Letavaj (Ed.), 18th Conference on Applied Mathematics proceedings. (pp. 304-312). Bratislava: Slovak University of Technology.
M. A. Ferreira, "LAPLACE transform effectiveness in the M/G/oo queue busy period probabilistic study", in 18th Conf. on Applied Mathematics proceedings, Dagmar Szarková, Daniela Richtáriková, Peter Letavaj, Ed., Bratislava, Slovak University of Technology, 2019, pp. 304-312
@inproceedings{ferreira2019_1732205826348, author = "Ferreira, M. A. M.", title = "LAPLACE transform effectiveness in the M/G/oo queue busy period probabilistic study", booktitle = "18th Conference on Applied Mathematics proceedings", year = "2019", editor = "Dagmar Szarková, Daniela Richtáriková, Peter Letavaj", volume = "", number = "", series = "", pages = "304-312", publisher = "Slovak University of Technology", address = "Bratislava", organization = "Slovak University of Technology in Bratislava-Faculty of Mechanical Engineering ", url = "http://evlm.stuba.sk/APLIMAT/indexe.htm" }
TY - CPAPER TI - LAPLACE transform effectiveness in the M/G/oo queue busy period probabilistic study T2 - 18th Conference on Applied Mathematics proceedings AU - Ferreira, M. A. M. PY - 2019 SP - 304-312 CY - Bratislava UR - http://evlm.stuba.sk/APLIMAT/indexe.htm AB - The Laplace transform is a widely used tool in the study of probability distributions, often allowing for a probability density functions and distribution functions simpler determination and being a “moments generating function”. In this paper, it is considered a situation not so simple, as it is the case of the M|G|∞ queue busy period length distribution. Attention will also be given the respective tail Laplace transform. Then, in the context of an open queues network, which nodes behave as M|G|∞ queues, the Laplace transform will be used to construct an algorithm to determine the Laplace transform of the global service time length of a customer during their stay on the network distribution. ER -